Data analysis involves understanding known facts or assumptions to draw conclusions about research questions. There are two main types of data analysis: qualitative and quantitative. Qualitative analysis examines subjective data like thoughts, feelings, and attitudes expressed in words, collected through interviews and observations. Quantitative analysis deals with numerical data, using statistical techniques to summarize relationships between variables. Both types of analysis require coding, organizing, and interpreting large amounts of data to understand the relevant information.
Presentation is made by the student of M.phil Jameel Ahmed Qureshi Faculty of Education Elsa Kazi campus Hyderabad UoS Jamshoron, This presentation is an assignment assign by the Dr. Mumtaz Khwaja
Presentation is made by the student of M.phil Jameel Ahmed Qureshi Faculty of Education Elsa Kazi campus Hyderabad UoS Jamshoron, This presentation is an assignment assign by the Dr. Mumtaz Khwaja
Quantitative Research: Surveys and ExperimentsMartin Kretzer
- Example lecture of the course "Methods and Theories in Information Systems"
- Target group: students who want to get an impression of the course before joining it
Practical Research 2 (Quantitative Research)Nheru Veraflor
Introduction to Practical Research 2 (Quantitative Research) for Senior High School. This includes lesson on Scientific Process, Characteristic of Quantitative Research and Types of Variables.
15 free qualitative and quantitative research methods booksThe Free School
15 free qualitative and quantitative research methods books for dissertation and thesis scholars. All books are available free-of-charge as open-access scholarships. The web addresses are provided. All books are accessible via Google or Google Scholar searches.
Quantitative Research: Surveys and ExperimentsMartin Kretzer
- Example lecture of the course "Methods and Theories in Information Systems"
- Target group: students who want to get an impression of the course before joining it
Practical Research 2 (Quantitative Research)Nheru Veraflor
Introduction to Practical Research 2 (Quantitative Research) for Senior High School. This includes lesson on Scientific Process, Characteristic of Quantitative Research and Types of Variables.
15 free qualitative and quantitative research methods booksThe Free School
15 free qualitative and quantitative research methods books for dissertation and thesis scholars. All books are available free-of-charge as open-access scholarships. The web addresses are provided. All books are accessible via Google or Google Scholar searches.
Data Presentation & Analysis Meaning, Stages of data analysis, Quantitative & Qualitative data analysis methods, Descriptive & inferential methods of data analysis
Get your quality homework help now and stand out.Our professional writers are committed to excellence. We have trained the best scholars in different fields of study.Contact us now at http://www.essaysexperts.net/ and place your order at affordable price done within set deadlines.We always have someone online ready to answer all your queries and take your requests.
data science course with placement in hyderabadmaneesha2312
360DigiTMG delivers data science course with placement in hyderabad, where you can gain practical experience in key methods and tools through real-world projects. Study under skilled trainers and transform into a skilled Data Scientist. Enroll today!
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
2. Data analysis is a process of understanding data or known facts or
assumptions serving as the basis of any claims or conclusions you
have about something. You collect these data in many ways:
observation, interview, documentary analysis, and research
instruments like questionnaires, test, etc. Your primary aim in analyzing
recorded data is to find out if they exist or operate to give answers to
the research questions you raised prior to your acts of collecting them.
In analyzing data, you go through coding and collating. Coding is your
act of using symbols like letters or words to represent arbitrary or
subjective data (emotions, opinions, attitudes) to ensure secrecy or
privacy of the data. Collating, on the other hand, is your way of brining
together the coded data. Giving the data an orderly appearance is
putting them in a graph, specifically a table of responses.
3. QUALITATIVE DATA ANALYSIS
In a qualitative research, you analyze or study data that reflect the
respondents’ thoughts, feelings, attitudes, or views about something.
These are subjective data that are expressed in words, and these
words serve as the unit in a qualitative type of research. You examine
these subjective data to understand how related or relevant they are to
your problems or specific research questions.
You collect data through interviews, observations or content analysis
and then subject them to data analysis. In your data collecting
activities, you indispensably experience a lot of things vis-à-vis the
source of data, such as their sizes, shapes, ideas, feelings, attitudes
4. and so on. If you record these data through verbal language or graphic
means, you get to immense yourself in a qualitative data analysis, not
quantitative data analysis, for the latter deals with data expressed in
numerical forms (Layder, 2013).
Qualitative data analysis is a time-consuming process. Data analysis in
a quantitative research is a rigorous act of thematic or theoretical
organization of ideas or information into a certain format that is capable
of presenting groups of responses.
5. QUANTITATIVE DATA ANALYSIS
All facts or information about people, places, things, events
and so on, and when these data appear not in words, images
or pictures, but in numerical forms such as fractions,
numbers and percentages, they become quantitative data.
It is time consuming because it involves series of
examinations, classifications, mathematical calculations, and
graphical recording, among others.
6. ▷STEPS IN QUANTITATIVE DATA ANALYSIS
Step 1: Preparing the Data
a. Coding System
- To analyze data means to quantify or change the verbally
expressed data into numerical information. Converting
words , images, or pictures into numbers. If not, it is very
impossible to do mathematical operations of division,
multiplication or subtraction.
Ex. a. Gender: 1 - male and 2 - female
b. Educational Attainment: 2 – elementary , 4 - high school
, 6 – college, 9 – MA and 12 for Ph.D. level
7. b. Data Tabulation
- For
easy classification
and distribution of
number based on a
certain criterion,
you have to collate
them with the help
of a graph called
Table.
Gender Male: 11 (46%)
Female: 13 (54%)
Course Fine Arts: 9 (37%)
Architecture: 6 (25%)
Journalism: 4 (17%)
Comm. Arts: 5 (20%)
Role in the 2016
Seminar Workshop on
Arts
Speaker: 4 (17%)
Organizer: 3 (12%)
Demonstrator: 5 (20%)
Participant: 12 (50%)
Attended in 2016 Arts
Summer Workshop
Yes: 18 (75%)
No: 6 (25%)
Sample Size - 24
8. Step 2: Analyzing the Data
Data coding and tabulation are the two important things you
have to do in preparing the data for analysis. Before immersing yourself
into studying every component of the data, decide on the kind of
quantitative analysis you have to use.
1. Descriptive Statistical Technique - provides a summary of the
orderly or sequential data obtained from the sample through the
data –gathering instrument used. The results of the analysis reveal
the following aspects of an item in a set of data (Morgan 2014;
Punch 2014; Walsh 2010):
Frequency Distribution – gives you the frequency of distribution
and percentage of the occurrence of an item in asset of data. In
other words, it gives you the number of responses given repeatedly
for one question.
9. Question: Do you find the Senators’ attendance in 2015
legislative sessions awful?
Measurement
Scale
Code Frequency
Distribution
Percent
Distribution
Strongly Agree 1 14 58%
Agree 2 3 12%
Neutral 3 2 8%
Disagree 4 1 4%
Strongly Disagree 5 4 17%
10. Measure of Central Tendency – indicates the different positions or
values of the items, such that in a category of data, you find an item or
items serving as the:
Mean – average of all the items or scores
Example: 3 +8 + 9 + 2 + 3 + 10 + 3
38/7 = 5.43
Median – the score in the middle of the set of items that cuts or
divides the set into two groups. (arranged from lowest to
highest) Example: 2, 3, 3, 3, 8, 9, 10 = 3
Mode – refers to the item or score in the data set that has the
most repeated appearance in the set.
Example: 3
11. Standard Deviation – shows the extent of the difference of the data
from the mean. An examination of this gap between the mean and the
data gives you an idea about the extent of the similarities and
differences between the respondents. These are mathematical
operations that you have to do to determine the standard deviation.
Step 1. Compute the Mean
Step 2. Compute the deviation (difference) between each
respondent’s answer (data item) and the mean. The plus (+) sign
appears before the number if the difference is higher; negative (-)
sign, if the difference is lower.
Step 3. Compute the square of each deviation.
Step 4. Compute the sum of squares by adding the squared figures.
12. Step 5. Divide the sum of squares by the number of data items to get
the variance.
Step 6. Compute the square root of variance figure to get standard
deviation.
Standard Deviation of the category of the data
collected from selected faculty members of one
university
Step 1: Mean: 7
(Step 2) (Step 3)
Date Item Deviation Square of Dev.
1 - 8 64
2 - 5 25
6 - 1 1
6 - 1 1
8 + 8 1
6 - 1 1
6 - 1 1
(Step 2) (Step 3)
Date Item Deviation Square of Dev.
14 + 7 49
16 + 9 81
Total: 317
Step 4: Sum of Squares: 317
Step 5: Variance = 36 (317 + 9)
Step 6: Standard Dev. – 6 (square root of 6)
13. 2. Advanced Quantitative Analytical Methods
An analysis of quantitative data that involves the use of more
complex statistical methods needing computer software like the SPSS,
STATA or MINTAB, among others, occurs graduate-level students
taking their MA of PhD degrees. Some of the advanced methods of
quantitative data analysis are the ff: (Argyrous 2011, Levin and Fox
2014; Godwin 2014):
a. Correlation – uses statistical analysis to yield results that can
describe the relationship of two variables. The results, however,
are incapable of establishing casual relationships.
b. Analysis of Variance (ANOVA) – the results of this statistical
analysis are sued to determine if the difference in the means or
averages of two categories of data are statistically significant.
14. Example: If the means of the grades of a student attending tutorial
lessons is significantly different from the mean of the grades of a
student not attending tutorial lessons.
c. Regression – has some similarities with correlation, in that, it also
shows the nature of relationship of variables, but gives more
extensive result than that of correlation. Aside from indicating the
presence of relationship between two variables, it determines
whether a variable is capable of predicting the strength of the
relation between the treatment (independent variable) and the
Outcome (dependent variable). Just like correlation, regression is
capable of establishing cause-effect relationship.
Example: If reviewing with music (treatment variable) is a
statistically significant predictor of the extent of the concept learning
(outcome variable) of a person.
15. ▷QUALITATIVE DATA ANALYSIS
In a qualitative research, you analyze or study data thatreflect the
respondents’ thoughts, feelings, attitudes, or views about something.
These are subjective data that are expressed in words, and these words
serve as the unit of analysis in a qualitative type of research. You examine
these subjective data to understand how related or relevant they are to
your problem or specific research questions.
You collect qualitative data through interviews, observations, or
content analysis and then subject them to data analysis. In your data
collecting activities, you indispensably experience a lot of things vis-à-vis
the sources of data, such as their sizes, shapes, ideas, feelings, attitudes,
an so on.
16. Data analysis is a process of understanding data or known facts or
assumptions serving as the basis of any claims or conclucions you have
about something. You collect these data in many ways: observation,
interview, documentary analysis, and research instruments like
questionnaires, test, etc. Your primary aim in analyzing recorded data is to
find out if they exist or operate to give answers to the research questions
you raised prior to your acts of collecting them.
In analyzing data, you go through coding and collating. Coding is your act
of using symbols like letters or words to represent arbitrary or subjective
data (emotions, opinions, attitudes) to ensure secrecy or privacy of the
data. Collating, on the other hand, is your way of brining together the
coded data. Giving the data an orderly appearance is putting them in a
graph, specifically a table of responses. If you record these data through
verbal language or graphic means, you get to immerse yourself in a
qualitative data analysis, not quantitative data
17. analysis, for the latter deals with data expressed in numerical forms.
(Lyder 2013).
Qualitative data analysis is a time-consuming process. It makes you
deal with data coming from wide sources of information. It is good if all the
data you collected from varies sources of knowledge work favorably for
your research study, but, ironically, some of these may not have strong
relations to your research questions. Data analysis in a qualitative
research is a rigorous act of thematic or theoretical organization of ideas
or information into a certain format that is capable of presenting groups of
responses. Analyzing the data and synthesizing them based on one
principle idea, theory, or pattern demand a lot of time and effort, let alone
the methodical ways you have to adhere to in presenting the results of a
long a written discussion containing verbal or graphical explanations of
your findings. (Letherby 2012; Silverman 2013; Litchman 2013)
18. ACTIVITY 5: C4 CRAFTING TIME
Chapter IV
Results and Findings
Sir Von Christopher Chua
Font style – Arial
Font size:
Chapter Name - 14, Bold
Title of the parts - 12, bold
Body - 11
Spacing - 1.5
Margin - Top, bottom, right – 1
- Left = 1.5